关键词: 单板节子彩色图像, 改进的彩色C-V模型, 多通道Gabor滤波器, 多目标分割

Abstract: Through analyzing the features of wood defects and the features of veneer knots, this paper presents an identification algorithm of wood defects, which is based on improved C-V colored model of multi-channel Gabor filters. This algorithm, which protects the colored information of the image, makes the colored image be an integral image. The algorithm applies multi-channel Gabor filters and K-means clustering to getting colored image, which is the discrimination of the defective target and the background. The algorithm applies the improved C-V colored model on the new image to abstracting the new image’s edge. To compare with the identification algorithm of gray image defects, which is based on improved C-V model and wavelet transformation, the results show that this method can segment the colored image of wood defects and the colored image of the multi-object veneer knot fast and accurately.

Key words: colored image of veneer knot, colored extension of C-V model, multi-channel Gabor filters, multi-object segmentation